Submitting Empirical to the ChatGPT app ecosystem
Submitted Empirical for ChatGPT app approval and tightened tooling metadata, test cases, and reviewer reliability.
ChatGPT app submission: reliability under review
App review stressed repeatability more than intent.
What surfaced
Small metadata mismatches, vague expected outputs, and stale assumptions caused compounded failures in reviewer workflows.
Review environments reward deterministic behavior, not optimistic assumptions.
What was tightened
- Tool annotation consistency.
- Stronger test case framing for shared demo environments.
- Clearer expected outcomes for stateful memory behavior.
- Test updates for create-or-merge behavior in shared reviewer accounts.
The result
Reviewer false failures dropped, and user-facing behavior became clearer.
Hard review constraints improved overall product quality beyond submission requirements.
Practical next steps
- Keep test fixtures aligned with reviewer-style shared accounts.
- Treat tool metadata drift as a release-blocking check.
- Add recurring submission smoke tests to prevent regression.